Onyango Isaac, Collinge Greg, Wang Yong, McEwen Jean-Sabin
The Gene and Linda Voiland School of Chemical Engineering and Bioengineering, Washington State University, Pullman, Washington 99163, United States.
Institute for Integrated Catalysis, Pacific Northwest National Laboratory, Richland, Washington 99354, United States.
J Phys Chem C Nanomater Interfaces. 2024 May 30;128(23):9504-9512. doi: 10.1021/acs.jpcc.4c01402. eCollection 2024 Jun 13.
Fe-based catalysts are highly selective for the hydrodeoxygenation of biomass-derived oxygenates but are prone to oxidative deactivation. Promotion with a noble metal has been shown to improve oxidative resistance. The chemical properties of such bimetallic systems depend critically on the surface geometry and spatial configuration of surface atoms in addition to their coverage (i.e., noble metal loading), so these aspects must be taken into account in order to develop reliable models for such complex systems. This requires sampling a vast configurational space, which is rather impractical using density functional theory (DFT) calculations alone. Moreover, "DFT-based" models are limited to length scales that are often too small for experimental relevance. Here, we circumvent this challenge by constructing DFT-parametrized lattice gas cluster expansions (LG CEs), which can describe these types of systems at significantly larger length scales. Here, we apply this strategy to Fe(100) promoted with four technologically relevant precious metals: Pd, Pt, Rh, and Ru. The resultant LG CEs have remarkable predictive accuracy, with predictive errors below 10 meV/site over a coverage range of 0 to 2 monolayers. The ground state configurations for each noble metal were identified, and the analysis of the cluster energies reveals a significant disparity in their dispersion tendency.
铁基催化剂对生物质衍生含氧化合物的加氢脱氧具有高度选择性，但容易发生氧化失活。已证明用贵金属促进可提高抗氧化性。除了表面原子的覆盖度（即贵金属负载量）之外，此类双金属体系的化学性质还严重依赖于表面原子的几何形状和空间构型，因此为了为此类复杂体系建立可靠模型，必须考虑这些方面。这需要对巨大的构型空间进行采样，仅使用密度泛函理论（DFT）计算是相当不切实际的。此外，“基于DFT”的模型仅限于长度尺度，而这些长度尺度对于实验相关性而言往往过小。在此，我们通过构建DFT参数化的晶格气体团簇展开（LG CEs）来规避这一挑战，该方法能够在大得多的长度尺度上描述此类体系。在此，我们将此策略应用于用四种具有技术相关性的贵金属（钯、铂、铑和钌）促进的Fe(100)。所得的LG CEs具有显著的预测准确性，在0至2个单层的覆盖范围内，预测误差低于10 meV/位点。确定了每种贵金属的基态构型，对团簇能量的分析揭示了它们在分散趋势上的显著差异。
